Siti Atiyah, Ali and Humaira, Nisar and Nurfaizatul Aisyah, Ab Aziz and Nor Asyikin, Fadzil and Nur Saida, Mohamad Zaber and Luthffi Idzhar, Ismail (2024) Understanding dyslexia and the potential of artificial intelligence in detecting neurocognitive impairment in dyslexia. In: Artificial Intelligence and Multimodal Signal Processing in Human-Machine Interaction : Artificial Intelligence Applications in Healthcare and Medicine. Academic Press, pp. 151-170. ISBN 978-0-443-29150-0
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Abstract
Dyslexia is a specific learning disorder that affects reading and writing abilities. Children with dyslexia are typically diagnosed during their primary school years, typically between the ages of 5 and 8, when their academic performance lags behind their peers. However, the diagnostic process can be lengthy, and due to the diverse range of characteristics exhibited by individuals with dyslexia, misdiagnosis as other learning disabilities is not uncommon. This delay in diagnosis can result in delayed intervention, further exacerbating their learning challenges. This chapter aims to provide an understanding of the clinical procedures involved in diagnosing dyslexia alongside current interventions, followed by a discussion of electrophysiological processing differences between children with dyslexia and typically developing children. This involves identifying significant abnormalities in neurocognitive processing activity in brain signals provided by electroencephalography (EEG) during the resting state and event-related potential (ERP) during different task stimulations. Taking significant abnormalities existing between dyslexia and healthy children into account, the current technology of artificial intelligence and machine learning as tools for diagnosing and intervening in dyslexia using multimodel of brain signals is considered beneficial to enable the development of methods for early diagnosis and tailored interventions for children with dyslexia as young as possible.
Item Type: | Book Chapter |
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Uncontrolled Keywords: | learning disorder, dyslexia, electroencephalography (EEG), event-related potential (ERP). |
Subjects: | T Technology > T Technology (General) |
Divisions: | Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development Faculties, Institutes, Centres > Faculty of Cognitive Sciences and Human Development Academic Faculties, Institutes and Centres > Faculty of Cognitive Sciences and Human Development |
Depositing User: | Ali |
Date Deposited: | 05 Dec 2024 08:25 |
Last Modified: | 05 Dec 2024 08:25 |
URI: | http://ir.unimas.my/id/eprint/46815 |
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